X-Ray imaging systems are frequently used during medical surgical procedures and interventions to provide physicians with image based information about the anatomical situation and/or the position and orientation of surgical instruments.
These devices typically provide two-dimensional projection images with different structures superimposed along the path of the X-rays.
A typical example of such a device for use in an intra-operative setting is the so-called C-arm used in a mobile or stationary manner and essentially consisting of a base frame on which a C-shaped arm is attached with several intermediate joints allowing moving the C-shaped arm in space along several degrees of freedom.
One end of the C-shaped arm carries an X-ray source and the other end an image detector.
Due to the limited information provided by these 2D images, 3D imaging techniques have become indispensable over the past decades.
While computer tomography is a well-established class of stationary X-ray imaging systems used for 3D reconstruction in a radiology department, these devices are in general not usable inside the operating room.
Recent years have seen an increasing interest in tomographic reconstruction techniques also known as cone-beam reconstruction techniques using two-dimensional detectors. Background information on these reconstruction techniques can be found, for example, in [1, 2].
Special efforts have been made to enable the abovementioned C-arms to provide three-dimensional information by automatically acquiring a set of 2D images and subsequent 3D image reconstruction based on said cone-beam reconstruction techniques [3-13].
Recently, so-called Cone-Beam Computer Tomography systems have been introduced to produce 3D images of patient parts, for example for dentistry applications, by simply creating a complete rotation of a source and an image plane contained inside a closed torus. This can be seen as a particular design of a C-arm.
In order to obtain high quality 3D images in terms of spatial resolution, geometric fidelity etc., it is essential to precisely know the projection geometry i.e. the position and orientation of the source and the detector in a common referential system for each 2D image used for the reconstruction.
However, while very well adapted to intra-operative 2D imaging tasks thanks to their manoeuvrability, C-arms, originally not designed for 3D imaging, are mechanically not sufficiently rigid to reproduce the desired projection geometry along a chosen path with sufficient accuracy due to their open gantry design.
The nominal trajectory of a C-arm during the automatic 2D image acquisition can be easily measured, for instance with encoders integrated in the joints.
However, the real trajectory differs from the nominal one for different reasons similar to the true kinematics and its nominal model in the field of robotics. The open gantry design makes the device prone to mechanical distortions such as bending depending on the current position/orientation. In particular, mobile C-arms are prone to collisions with doors or other objects while moved around, resulting in non-elastic deformations of the C-arm. Depending on the type of bearing and drive of the C-arm, wobbling of the C-arm cannot be avoided due to its own mass and the masses of the x-ray source and x-ray detector altering the nominal trajectory thus leading, as a geometry error, to limitation of the spatial resolution of the reconstructed 3D image.
To overcome these problems, different methods are known from the literature for calibrating the imaging geometry of the C-arm i.e. to measure the projection geometry for the trajectory used for acquiring the images.
The term projection geometry, as used here, encompasses the detector position and orientation, as well as the X-ray source position relative to a common referential system.
A common technique consists in using a well-defined calibration phantom that allows precise determination of the entire projection geometry for each image taken throughout a scan, such that the predicted marker projections based on that geometry and a model of the phantom optimally match the locations of the markers identified in the image. Such a calibration phantom, which is rather cumbersome due to its required volumetric expansion to allow determination of the entire projection geometry, can be used either online (i.e. during each diagnostic use) or offline (i.e. not during diagnostic use).
In practice, the general approach to offline calibrating an imaging system consists in performing an image acquisition of a specific calibration phantom containing radiopaque markers prior to the diagnostic image acquisition. The phantom remains stationary during the scan. The projection images are then evaluated in a pre-processing step in order to extract marker shadow locations and correspondences from the images. This is followed by the calibration step itself, which establishes the optimal estimate of the projection geometry for each projection, usually based on an estimation error metric which is often the root-mean-square error between the detected and the predicted marker shadow locations, based on the current estimate of the projection geometry.
U.S. Pat. Nos. 6,715,918 and 5,442,674 disclose such an offline calibration phantom consisting essentially of a radio-transparent cylindrical tube with radiopaque markers of different size attached to its circumference at precisely known positions. During the calibration process, a series of images is taken throughout the trajectory chosen for image acquisition with the phantom being placed such that the markers are visible in all images without repositioning the phantom. Using well-known image processing methods, marker centers are calculated in the projection images and labelled, i.e. assigned to the corresponding marker in the phantom having caused the shadow in the image. With sufficient marker centers calculated and assigned, the projection geometry for all images can then be computed in a common referential system.
Calibration with such an offline phantom is typically carried out once before the first clinical use of the system and subsequently at longer or shorter intervals, e.g. every 6 months. By its nature this method deals well with reproducible deviations.
On the other hand, irreproducible deviations of the projection geometry like thermal shifts, fatigue over time, mechanical deformations due to collisions of the device during use or transport cannot be compensated for.
Since deviations can only be detected during the offline calibration, there is a risk that at one point in time, between two recurring offline calibrations, the 3D images will lack the accuracy necessary for clinical use. Another drawback of offline calibration methods is to restrict the use of the C-arm for 3D reconstruction to only one trajectory, i.e. the one that has been calibrated.
In order to allow compensation for irreproducible errors as well, different online calibration methods are known from the literature.
These methods aim at performing the calibration during the diagnostic image scan of the device, using a phantom made of radiopaque markers that are placed in the volume to be acquired and reconstructed as a 3D image.
One of the general problems with such an online calibration method based on radiopaque markers aiming at a full calibration, i.e. determining the complete projection geometry for each acquired image, is the fact that for diagnostic imaging, the C-arm is positioned such that the anatomical region of interest (ROI) is visible on each image.
Since the phantom can obviously not be placed exactly in the same position, it is usually difficult—if not impossible—to ensure the visibility of the phantom in all images, thus often not allowing a full calibration.
Another problem is that radiopaque or very radio-dense objects such as metal parts of the operating table, surgical instruments, implants etc. may occlude one or more of the phantom markers in one or more of the images.
U.S. Pat. No. 6,038,282 aims at solving this problem by positioning an online arc-shaped phantom around the patient, essentially working in the same manner as the offline calibration method described above. However, while providing potentially good calibration accuracy, this phantom significantly obstructs the surgical access to the patient and is very cumbersome and expensive to manufacture and maintain with high mechanical accuracy.
To overcome these problems other methods for online calibration have been proposed.
U.S. Pat. No. 6,079,876 discloses a method for online calibration based on optical cameras attached to both ends of the C-shaped arm allowing determination of the position and orientation of both the detector and the source with respect to an optical marker ring positioned around the operating table. The marker ring required in this method complicates the access to the patient and must be repositioned each time the C-arm position or orientation is adjusted.
U.S. Pat. No. 6,120,180 discloses a method for online calibration using an ultrasound or electromagnetic tracking system in order to capture the position and orientation of both the source and the detector. This system is prone to occlusion and magnetic field distortion problems as well as ergonomic restriction preventing these systems from being used in a clinical environment.
DE 10139343 discloses a method for online calibration based on strain gauges to measure the deflection of the C-arm. This method is complex to manage and maintain with a high degree of accuracy over time, and it cannot recover the full projection geometry and captures only some deformations.
U.S. Pat. No. 7,494,278 discloses a calibration method that dispenses with any additional measuring equipment by seeking to use natural features in the projection images themselves to detect and correct for trajectory deviations visible in sinograms. While this method could in theory be effective, it is not revealed how image features to be tracked in sinograms are identified. No method for detecting such natural features with a high degree of precision and reproducibility is described, which makes it non-usable in reality.
Accordingly, the present invention is intended to improve the quality of reconstructed 3D image by overcoming at least one of the above disadvantages.